Closed-form solvers in few-shot learning: The use of closed-form solvers for few-shot classification is also not entirely new, though to our knowledge they have not been applied in the explicit context of feature reconstruction.
 [1]} uses ridge regression to map features directly to classification labels, while [2]} accomplishes the same mapping with differentiable SVMs.
Deep Subspace Networks [3]} use the closed-formed projection distance from query embeddings to subspaces spanned by support points as the similarity measure.
In contrast, FRN uses closed-form ridge regression to reconstruct entire feature maps, rather than performing direct comparisons between single points in latent space, or regressing directly to class label targets.
